Effective new strategies for the prevention and treatment of cancer will depend upon the detailed understanding of cancer evolution through its progressive stages at both the genomic and molecular levels. Since it is particularly difficult to study such changes in the human population, my laboratory has focused on the application of animal models of mammary and prostate cancer for understanding molecular processes involved in the development of these cancers and the judicious utilization of appropriate models for translational studies. The research efforts of my laboratory have focused on dissecting dynamic changes in genome organization and gene expression that occur during cancer progression in rodent models of mammary and prostate cancer and to use this information to understand how to better prevent or inhibit the oncogenic process. An important aspect of this work is to determine on a molecular level how similar various models are to the human cancers that they are thought to represent. The fundamental premise of our work is that cancer does not result from the dysregulation of a single gene, but rather from multiple, complex coordinated interactions that allow cells to grow and metastasize to a foreign habitat, ultimately killing the patient. In order to begin to decipher such complexity through a systems biology approach, my laboratory utilizes high throughput molecular techniques to amass large datasets that can be used to identify sets of genes whose collective expression correlates to genetic and biologic properties of our experimental systems. Functional testing of candidate genes is subsequently performed to validate the biologic role of particular genes. This process may be iterative.In order to accomplish these goals, I have sought to answer fundamental scientific questions about mammary and prostate cancer models with the ultimate goal of comparing these findings to the human diseases: What genes are dysregulated in cancer compared to normal tissue? Does the initiating oncogenic event determine the gene expression signature of a tumor and, if so, what critical distinguishing pathways are represented? What are the fundamental molecular differences between tumors that originate through the over-expression of an oncogene, the loss of a suppressor gene, or induction by chemical carcinogens? Can this information be utilized to choose appropriate models to answer specific experimental questions? Can we identify previously unrecognized genes that may have important functions related to cancer progression, particularly those involved in metastases? What improvements in informatics approaches will help to uncover answers to these and other important questions using extremely large datasets? Significant progress has been made in each of these areas as described below. My laboratory was the first to publish comprehensive expression array datasets for major mouse models of mammary cancer (1). Analyses have identified common "cancer genes" as well as expression signatures related to the initiating oncogenic event leading to the in depth functional study of several genes and the cloning of a novel gene potentially related to tumorigenesis involving her2/neu. Important observations about changes in gene expression during cancer progression have also been made. While genomics provides an important means of validating models, the identification of critical, homologous cancer pathways between species will lead to recognition of important targets for therapy and improved modeling of these cancers in animals. Tumor progression in both the mammary and prostate glands is often associated with a progression from a hormone-responsive to a hormone-independent state (2, 3). In order to understand what hormone-related signaling pathways may be involved in this biologic transition, my laboratory has used expression profiling to define in vivo hormone-responsive genes for both target tissues. The goals of these studies are twofold: First, to determine which hormone-responsive genes and their associated pathways are dysregulated in prostate and mammary cancers and whether this leads to a growth advantage for the tumor cells; and second, to combine this information with publicly available datasets (CGAP, MGAP, SAGE, published array data, etc.) to identify tissue-specific, hormone-independent genes which may be useful for gene targeting to the mammary or prostate epithelium.While understanding mechanisms of oncogenesis should lead to the identification of additional targets for therapy, my laboratory has also pursued complementary approaches to evaluate stage-specific biological responses to compounds that may prevent, inhibit or reduce the burden of mammary cancer (4-13). We have focused these efforts on several classes of preventive agents and compounds that inhibit tumor vascularization. The use of relevant animal models may be particularly well suited to answer experimentally several important questions: How do genetically-engineered mouse models respond to chemopreventive and therapeutic agents and how does this relate to the genetic abnormalities used to develop the tumors? Do the agents work in a cancer stage-specific manner? Are there agents that target dormant metastatic cells? Will the application of high-throughput genomic approaches identify previously unrecognized in vivo mechanisms of action for various compounds that may lead to improved choices for combination therapy? Can array approaches help identify mechanisms of resistance to therapy? Several long-term studies have been performed testing multiple chemopreventive and anti-angiogenic compounds and have resulted in a range of responses that appear to be stage-specific. Ongoing studies are determining compound-specific gene expression signatures and will lead to rationale combination therapies. Future studies will focus on identifying and testing compounds that prevent or inhibit tumorigenesis in mammary models that incorporate genomic instability as a key feature. In summary, my research program is helping to achieve major objectives of the NCI through our work to understand cancer from a systems biology perspective, identifying genes that are involved in tumor progression and metastases that may serve as important targets for therapy, and advancing the applications of animal models for pre-clinical testing.